Facial recognition is typically performed by a software application that automatically identifies a person from a digital image (including a video frame) by comparing selected facial features from the digital image to a facial database.
Facial recognition is typically deployed for security reasons and therefore accuracy is of paramount importance. The accuracy of facial recognition, however, may suffer when the facial recognition software attempts to perform facial recognition matching of an image of a person taken in a crowd to a facial database having known facial images, where the captured image is influenced by image quality, capture angle, and the person's immediate appearance (e.g., glasses, hat, facial hair, and the like). In this case, the software must attempt to match the captured image with a potentially large number of known images, thereby decreasing the speed and/or accuracy of potential matches.
Accordingly, it would be desirable to provide a method and system for prioritizing facial recognition matching.